The present invention relates to an electronic fingerprint identification device. More specifically, the present invention relates to a stand-alone, low-power, portable electronic fingerprint identification device featuring fingerprint identification algorithms that are designed to minimize the use of computationally intensive operations.
Biometric devices such as fingerprint identification devices have become increasingly popular in recent years, their most common uses being for security and access control. They are considered more secure than personal identification (PIN) numbers or cards because a fingerprint cannot be forged and possession of a fingerprint cannot be transferred.
There has also been a heightened demand among consumers for increased portability in computing, communications, and other devices for which access control is necessary or desirable. Among other developments there has been a proliferation of portable communication, computing and network interface devices such as personal digital assistants (xe2x80x9cPDAsxe2x80x9d), beepers, pages, information appliances, Internet access devices and the like. However, existing fingerprint identification devices are not generally designed to interface with such existing devices, and do not typically include the stand-alone, low-power capabilities desired for portable devices.
Existing fingerprint devices generally scan a fingerprint and transmit the image through a serial connection to a personal computer (PC). However, these devices require the use of software that is installed on PC having at least a PENTIUM(copyright) class microprocessor operating at 200 MHz or more in order to process the fingerprint image and perform enrollment, verification, and database functions. More particularly, known algorithms for performing such functions are sufficiently computationally intensive that only a relatively powerful microprocessor can perform the operations necessary to identify a fingerprint in a commercially reasonable period of time. For instance, known algorithms use functions such as Fourier transforms, and complete image-to-image comparisons, which require substantial computing power to execute in a reasonable period of time. Requiring a PC to process the fingerprint image adds to the expense of such devices makes them unusable by owners of portable computing, communication and other devices, and generally diminishes the applications in which they can be used.
Also known in the art are fingerprint identification devices that contain embedded or autonomous fingerprint capture and verification software and thus do not require a PC to process the fingerprint image, such as the Sony(copyright) FIU fingerprint identification unit. The power requirements of these devices are substantial and require an external power supply, which diminishes their portability and convenience and their usability with PDAs, cellular telephones, and other portable devices. As such, these devices cannot be considered to operate on a xe2x80x9cstandalonexe2x80x9d basis.
At least one attempt has been made to design a portable, battery powered, stand-alone biometric (including fingerprint) identification device, as described in International Application WO 99/56429, assigned to Identix Incorporated. Unfortunately, because of the RISC microprocessor, DRAM memory and A/D converter, the peak power consumption is estimated to be on the order of 4.3 Watts (xe2x80x9cWxe2x80x9d). This power consumption is substantially in excess of what is commercially acceptable for many applications. Indeed, for many applications it is essential the fingerprint identification device operate on low-cost batteries that can operate for extended periods of time, i.e., weeks to months, without replacement. To achieve this goal, and provide fingerprint identification with a high degree of accuracy, it is desirable that peak power consumption of portable, stand-alone fingerprint devices not exceed about 1 W. The computationally intensive nature of known fingerprint identification algorithms and the power consumption demands of existing memory and processor devices has, it is believed, made attainment of this objective an impossibility.
Thus, there exists a need in the art for a stand-alone, low-power, battery-operated, compact device that is capable of verifying and/or enrolling a fingerprint relative quickly and with a high degree of accuracy.
One aspect of the present invention is a biometric verification device for providing secure access to a unit connected to the device. The device includes a biometric sensor capable of sensing a biometric trait of a user that is unique to the user and providing a first signal containing information representing the biometric trait. The device also includes a processing unit connected to the biometric sensor so as to receive the first signal. The processing unit is adapted to compare the information with biometric data stored in the processing unit representing a biometric trait of an enrolled person, and provide a verification signal indicating whether or not the information corresponds sufficiently with the biometric data to verify the user is the enrolled person. The processing unit completes the comparison and generates the verification signal within 20 seconds of when the biometric sensor senses the biometric trait using no more than 1 W of peak power.
Another aspect of the present invention is a system for extracting fingerprint minutia points from a first monochrome image containing an x-y array of pixels, each representing either a fingerprint ridge or a fingerprint valley. The x-y array is divided into a plurality of contiguous local blocks, each having a predetermined number of the pixels arranged in rows and columns. Each minutia point is one of several types. The system includes a scanner module that scans lines of pixels in each local block to detect the position of segments of pixels in each local block representing a fingerprint ridge. Also included is a comparator module that compares each of the ridge segments detected by the scanner module in each local block with adjacent ridge segments to determine if a minutia point exists, and identifies its position and minutia point type. The system further includes a ridge direction module that determines direction of fingerprint ridges leading to each minutia point determined by the comparator module, and a minutia list module that saves the position and type of minutia points determined by the comparator module and fingerprint ridge directions determined by the ridge direction module.
Yet another aspect of the present invention is a fingerprint identification device that includes a sensor for providing an output signal containing information representing attributes of a user""s fingerprint positioned proximate the sensor that are unique to the user. The device also includes a memory for storing a first template containing attributes of a fingerprint of a first person that are unique to the first person and a logic unit connected to the memory. A program is stored in the memory that, in cooperation with the memory and logic unit: (i) creates the first template using the information in the output signal from the fingerprint sensor that represents unique attributes of the first person""s fingerprint positioned proximate the sensor; (ii) creates a second template using the information in the output signal from the fingerprint sensor that represents in less than 1 K bytes of data unique attributes of a user""s fingerprint positioned proximate the sensor; and (iii) verifies if the user is the first person by attempting to match the unique attributes in the first template with the unique attributes in the second template.
Still another aspect of the present invention is a method of creating a template containing attributes of a fingerprint unique to a first person, the fingerprint having a plurality of minutia points of one or more types and a ridge leading to each of the minutia points. The method comprises the steps of (a) identifying the location and type of a plurality of minutia points on the fingerprint, (b) identifying the direction of the ridge leading to each minutia point, and (c) using no more than 1 K bytes of data, storing the location and type of the minutia points identified in step a and the direction of the ridge leading to each minutia point identified in step b.